EEG–EMG coupling as a hybrid method for steering detection in car driving settings

AbstractUnderstanding mental processes in complex human behavior is a key issue in driving, representing a milestone for developing user-centered assistive driving devices. Here, we propose a hybrid method based on electroencephalographic (EEG) and electromyographic (EMG) signatures to distinguish left and right steering in driving scenarios. Twenty-four participants took part in the experiment consisting of recordings of 128-channel EEG and EMG activity from deltoids and forearm extensors in non-ecological and ecological steering tasks. Specifically, we identified the EEG mu rhythm modulation correlates with motor preparation of self-paced steering actions in the non-ecological task, while the concurrent EMG activity of the left (right) deltoids correlates with right (left) steering. Consequently, we exploited the mu rhythm de-synchronization resulting from the non-ecological task to detect the steering side using cross-correlation analysis with the ecological EMG signals. Results returned significant cross-correlation values showing the coupling between the non-ecological EEG feature and the muscular activity collected in ecological driving conditions. Moreover, such cross-correlation patterns discriminate the steering side earlier relative to the single EMG signal. This hybrid system overcomes the limitation of the EEG signals collected in ecological settings such as low reliability, accuracy, and adaptability, thus adding to the EMG the characteristic predictive power of the cerebral data. These results prove how it is possible to complement different physiological signals to control the level of assistance needed by the driver.

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Hybrid EEG-EMG system to detect steering actions in car driving settings

10.1101/2021.09.16.460615 ◽

2021 ◽

Author(s):

Giovanni Vecchiato ◽

Maria Del Vecchio ◽

Jonas Ambeck-Madsen ◽

Luca Ascari ◽

Pietro Avanzini

Keyword(s):

Cross Correlation ◽

Predictive Power ◽

Muscular Activity ◽

Motor Preparation ◽

Emg Activity ◽

Mu Rhythm ◽

Eeg Signals ◽

Emg Signal ◽

Cross Correlation Analysis ◽

Car Driving

Understanding mental processes in complex human behaviour is a key issue in the context of driving, representing a milestone for developing user-centred assistive driving devices. Here we propose a hybrid method based on electroencephalographic (EEG) and electromyographic (EMG) signatures to distinguish left from right steering in driving scenarios. Twenty-four participants took part in the experiment consisting of recordings 128-channel EEG as well as EMG activity from deltoids and forearm extensors in non-ecological and ecological steering tasks. Specifically, we identified the EEG mu rhythm modulation correlates with motor preparation of self-paced steering actions in the non-ecological task, while the concurrent EMG activity of the left (right) deltoids correlates with right (left) steering. Consequently, we exploited the mu rhythm de-synchronization resulting from the non-ecological task to detect the steering side by means of a cross-correlation analysis with the ecological EMG signals. Results returned significant cross-correlation values showing the coupling between the non-ecological EEG feature and the muscular activity collected in ecological driving conditions. Moreover, such cross-correlation patterns discriminate left from right steering with an earlier dynamic with respect to the single EMG signal. This hybrid system overcomes the limitation of the EEG signals collected in ecological settings such as low reliability, accuracy and adaptability, thus adding to the EMG the characteristic predictive power of the cerebral data. These results are a proof of concept of how it is possible to complement different physiological signals to control the level of assistance needed by the driver.

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Single-Neuron Analysis of Human Thalamus in Patients With Intention Tremor and Other Clinical Signs of Cerebellar Disease

Journal of Neurophysiology ◽

10.1152/jn.00049.2001 ◽

2002 ◽

Vol 87 (4) ◽

pp. 2084-2094 ◽

Cited By ~ 30

Author(s):

F. A. Lenz ◽

C. J. Jaeger ◽

M. S. Seike ◽

Y. C. Lin ◽

S. G. Reich

Keyword(s):

Neuronal Activity ◽

Cross Correlation ◽

Clinical Signs ◽

Emg Activity ◽

Phase Lag ◽

Cerebellar Disease ◽

Intention Tremor ◽

Cross Correlation Analysis ◽

Relay Nucleus ◽

Cerebellar Tremor

Tremor that occurs as a result of a cerebellar lesion, cerebellar tremor, is characteristically an intention tremor. Thalamic activity may be related to cerebellar tremor because transmission of some cerebellar efferent signals occurs via the thalamus and cortex to the periphery. We have now studied thalamic neuronal activity in a cerebellar relay nucleus (ventral intermediate—Vim) and a pallidal relay nucleus (ventralis oral posterior—Vop) during thalamotomy in patients with intention tremor and other clinical signs of cerebellar disease (tremor patients). The activity of single neurons and the simultaneous electromyographic (EMG) activity of the contralateral upper extremity in tremor patients performing a pointing task were analyzed by spectral cross-correlation analysis. EMG spectra during intention tremor often showed peaks of activity in the tremor-frequency range (1.9–5.8 Hz). There were significant differences in thalamic neuronal activity between tremor patients and controls. Neurons in Vim and Vop had significantly lower firing rates in tremor patients than in patients undergoing thalamic surgery for pain (pain controls). Other studies have shown that inputs to Vim from the cerebellum are transmitted through excitatory connections. Therefore the present results suggest that tremor in these tremor patients is associated with deafferentation of the thalamus from cerebellar efferent pathways. The thalamic X EMG cross-correlation functions were studied for cells located in Vim and Vop. Neuronal and EMG activity were as likely to be significantly correlated for cells in Vim as for those in Vop. Cells in Vim were more likely to have a phase lag relative to EMG than were cells in Vop. In monkeys, cells in the cerebellar relay nucleus of the thalamus, corresponding to Vim, are reported to lead movement during active oscillations at the wrist. In view of these monkey studies, the present results suggest that cells in Vim are deafferented and have a phase lag relative to tremor that is not found in normal active oscillations. The difference in phase of thalamic spike X EMG activity between Vim and Vop may contribute to tremor because lesions of pallidum or Vop are reported to relieve cerebellar tremor.

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Cross-Correlation Analysis of Thalamic Neurons and EMG Activity in Parkinsonian Tremor

Stereotactic and Functional Neurosurgery ◽

10.1159/000101148 ◽

1985 ◽

Vol 48 (1-6) ◽

pp. 305-308 ◽

Cited By ~ 1

Author(s):

F.A. Lenz ◽

R.R. Tasker ◽

H.C. Kwan ◽

S. Schnider ◽

R. Kwong ◽

...

Keyword(s):

Correlation Analysis ◽

Cross Correlation ◽

Emg Activity ◽

Thalamic Neurons ◽

Parkinsonian Tremor ◽

Cross Correlation Analysis

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Joint cross-correlation analysis reveals complex, time-dependent functional relationship between cortical neurons and arm electromyograms

Journal of Neurophysiology ◽

10.1152/jn.00031.2013 ◽

2014 ◽

Vol 112 (11) ◽

pp. 2865-2887 ◽

Cited By ~ 6

Author(s):

Katie Z. Zhuang ◽

Mikhail A. Lebedev ◽

Miguel A. L. Nicolelis

Keyword(s):

Cortical Neurons ◽

Cross Correlation ◽

Cortical Activity ◽

Emg Activity ◽

Brain Machine Interfaces ◽

Dynamic Task ◽

Cortical Areas ◽

Arm Reaching ◽

Cross Correlation Analysis ◽

Neurophysiological Studies

Correlation between cortical activity and electromyographic (EMG) activity of limb muscles has long been a subject of neurophysiological studies, especially in terms of corticospinal connectivity. Interest in this issue has recently increased due to the development of brain-machine interfaces with output signals that mimic muscle force. For this study, three monkeys were implanted with multielectrode arrays in multiple cortical areas. One monkey performed self-timed touch pad presses, whereas the other two executed arm reaching movements. We analyzed the dynamic relationship between cortical neuronal activity and arm EMGs using a joint cross-correlation (JCC) analysis that evaluated trial-by-trial correlation as a function of time intervals within a trial. JCCs revealed transient correlations between the EMGs of multiple muscles and neural activity in motor, premotor and somatosensory cortical areas. Matching results were obtained using spike-triggered averages corrected by subtracting trial-shuffled data. Compared with spike-triggered averages, JCCs more readily revealed dynamic changes in cortico-EMG correlations. JCCs showed that correlation peaks often sharpened around movement times and broadened during delay intervals. Furthermore, JCC patterns were directionally selective for the arm-reaching task. We propose that such highly dynamic, task-dependent and distributed relationships between cortical activity and EMGs should be taken into consideration for future brain-machine interfaces that generate EMG-like signals.

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Motor Patterns for Human Gait: Backward Versus Forward Locomotion

Journal of Neurophysiology ◽

10.1152/jn.1998.80.4.1868 ◽

1998 ◽

Vol 80 (4) ◽

pp. 1868-1885 ◽

Cited By ~ 207

Author(s):

R. Grasso ◽

L. Bianchi ◽

F. Lacquaniti

Keyword(s):

Time Course ◽

Cross Correlation ◽

Gait Cycle ◽

Human Gait ◽

Emg Activity ◽

Ground Reaction Forces ◽

Motor Patterns ◽

Cross Correlation Analysis ◽

Reaction Forces ◽

Forward Locomotion

Grasso, R., L. Bianchi, and F. Lacquaniti. Motor patterns for human gait: backward versus forward locomotion. J. Neurophysiol. 80: 1868–1885, 1998. Seven healthy subjects walked forward (FW) and backward (BW) at different freely chosen speeds, while their motion, ground reaction forces, and electromyographic (EMG) activity from lower limb muscles were recorded. We considered the time course of the elevation angles of the thigh, shank, and foot segments in the sagittal plane, the anatomic angles of the hip, knee, and ankle joints, the vertical and longitudinal ground reaction forces, and the rectified EMGs. The elevation angles were the most reproducible variables across trials in each walking direction. After normalizing the time course of each variable over the gait cycle duration, the waveforms of all elevation angles in BW gait were essentially time reversed relative to the corresponding waveforms in FW gait. Moreover, the changes of the thigh, shank, and foot elevation covaried along a plane during the whole gait cycle in both FW and BW directions. Cross-correlation analysis revealed that the phase coupling among these elevation angles is maintained with a simple reversal of the delay on the reversal of walking direction. The extent of FW–BW correspondence also was good for the hip angle, but it was smaller for the knee and ankle angles and for the ground reaction forces. The EMG patterns were drastically different in the two movement directions as was the organization of the muscular synergies measured by cross-correlation analysis. Moreover, at any given speed, the mean EMG activity over the gait cycle was generally higher in BW than in FW gait, suggesting a greater level of energy expenditure in the former task. We argue that conservation of kinematic templates across gait reversal at the expense of a complete reorganization of muscle synergies does not arise from biomechanical constraints but may reflect a behavioral goal achieved by the central networks involved in the control of locomotion.

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EMG Muscle Activation Pattern of Four Lower Extremity Muscles during Stair Climbing, Motor Imagery, and Robot-Assisted Stepping: A Cross-Sectional Study in Healthy Individuals

BioMed Research International ◽

10.1155/2019/9351689 ◽

2019 ◽

Vol 2019 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Damaris E. Geiger ◽

Frank Behrendt ◽

Corina Schuster-Amft

Keyword(s):

Motor Imagery ◽

Cross Correlation ◽

Stair Climbing ◽

Emg Activity ◽

Healthy Individuals ◽

Robot Assisted ◽

Tilt Table ◽

Imagery Condition ◽

Gastrocnemius Medialis ◽

Cross Correlation Analysis

Background. Stair climbing can be a challenging part of daily life and a limiting factor for social participation, in particular for patients after stroke. In order to promote motor relearning of stair climbing, different therapeutical measures can be applied such as motor imagery and robot-assisted stepping therapy. Both are common therapy measures and a positive influence on the rehabilitation process has been reported. However, there are contradictory results regarding the neuromuscular effect of motor imagery, and the effect of robot-assisted tilt table stepping on the EMG activation compared to stair climbing itself is not known. Thus, we investigated the EMG activity during (1) a stepping task on the robot-assisted tilt table Erigo, (2) motor imagery of stair climbing, and (3) real stair climbing in healthy individuals for a subsequent study on patients with lower limb motor impairment. The aim was to assess potential amplitude independent changes of the EMG activation as a function of the different conditions.Methods. EMG data of four muscles of the dominant leg were recorded in m. rectus femoris, m. biceps femoris, m. tibialis anterior, and m. gastrocnemius medialis. The cross-correlation analysis was performed to measure similarity/dissimilarity of the EMG curves.Results. The data of the study participants revealed high cross-correlation coefficients comparing the EMG activation modulation of stair climbing and robot-assisted tilt table stepping in three muscles except for the m. gastrocnemius medialis. As the EMG activation amplitude did not differ between motor imagery and the resting phase the according EMG data of the motor imagery condition were not subjected to a further analysis.Conclusion. Robot-assisted tilt table stepping, but rather not motor imagery, evokes a similar activation in certain leg muscles compared to real stair climbing.

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